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An Improved Design Methodology for Reconfigurable Robots During COVID 19 Pandemic at University: Robocov Case Study at Tecnologico de Monterrey
Machine Learning-Driven Digital Technologies for Educational Innovation Workshop ; 2021.
Article in English | Web of Science | ID: covidwho-1895913
ABSTRACT
Developing a mechatronic system involves designing and implementing different subsystems involving multiple engineering areas, giving the system a high level of complexity. Thus, the design methodology is critical in developing multidisciplinary mechatronic products. The V-model is one of the most used methodologies by industry and academia. The three-part design structure facilitates rapid prototyping system design, domain-specific design process, and system integration;these consider consumer requirements as the initial inputs. Nowadays, universities require dynamic design methodologies to develop new skills and competencies in their students. Hence, improvements of design methodologies must be adopted in various educational models, such as the Tec-21 model at Tecnologico de Monterrey. This educational model uses challenges in its pedagogical approach, actively involving students in current, relevant problem situations like the COVID-19 pandemic. This paper describes the development of a multitasking, modular, teleoperated robot named Robocov, a mechatronic V model product, as described in VDI guideline 2206, using a fuzzy cluster decision system to empower the methodology. This robot is a mobile teleoperated platform that can utilize various adaptable modules. Depending on the module, it can develop different activities and solve multiple tasks. Due to the current pandemic, the first developed modules were programmed with tasks focusing on sanitizing closed and open spaces and monitoring health standards and protocols.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Case report Language: English Journal: Machine Learning-Driven Digital Technologies for Educational Innovation Workshop Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Case report Language: English Journal: Machine Learning-Driven Digital Technologies for Educational Innovation Workshop Year: 2021 Document Type: Article